Effects of enzymes on organic matter conversion in anaerobic fermentation of sludge to produce volatile fatty acids.

Sludge hydrolysis is a vital step in anaerobic digestion of sludge. This study compared the efficacy of free versus immobilized enzymes at different concentrations in promoting sludge disintegration. Pretreatment with 1,000 mg/L immobilized enzymes was more efficient in promoting sludge disintegration than free enzymes at the same concentration. Under the optimized conditions, volatile fatty acids (VFAs) were produced at 10.6 g/L, accounting for 85 % of total soluble chemical oxygen demand. Improved VFA production was attributed to the release of large amounts of polysaccharides and proteins from the enzymatically pretreated sludge. Released organic matter are the substrates for VFAs generated by the determined microbial community of Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, and Chloroflexi. In this study, anaerobic fermentation was used to successfully convert organic matter in sludge into high-value-added VFAs. Therefore, this process can be selected as a strategy to reduce carbon emissions from wastewater treatment plants (WWTPs).

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis and treatment are of great significance. Due to the lack of timely and effective fundus screening for premature infants in remote areas, leading to an aggravation of the disease and even blindness, in this paper, a deep learning-based collaborative edge-cloud telemedicine system is proposed to mitigate this issue. In the proposed system, deep learning algorithms are mainly used for classification of processed images. Our algorithm is based on ResNet101 and uses undersampling and resampling to improve the data imbalance problem in the field of medical image processing. Artificial intelligence algorithms are combined with a collaborative edge-cloud architecture to implement a comprehensive telemedicine system to realize timely screening and diagnosis of retinopathy of prematurity in remote areas with shortages or a complete lack of expert medical staff. Finally, the algorithm is successfully embedded in a mobile terminal device and deployed through the support of a core hospital of Guangdong Province. The results show that we achieved 75% ACC and 60% AUC. This research is of great significance for the development of telemedicine systems and aims to mitigate the lack of medical resources and their uneven distribution in rural areas.